1.2k citations · 2.6k across the 21 of their papers we have counts for
4 papers · 1 filter
Benchmarking Language Models for Code Syntax Understanding
Da Shen, Xinyun Chen, Chenguang Wang +2
Pre-trained language models have demonstrated impressive performance in both natural language processing and program understanding, which represent the input as a token sequence wi…
Scaling Instruction-Finetuned Language Models
Hyung Won Chung, Le Hou, Shayne Longpre +32
Finetuning language models on a collection of datasets phrased as instructions has been shown to improve model performance and generalization to unseen tasks. In this paper we expl…
Compositional Semantic Parsing with Large Language Models
Andrew Drozdov, Nathanael Schärli, Ekin Akyürek +5
Humans can reason compositionally when presented with new tasks. Previous research shows that appropriate prompting techniques enable large language models (LLMs) to solve artifici…
Measuring and Improving Compositional Generalization in Text-to-SQL via Component Alignment
Yujian Gan, Xinyun Chen, Qiuping Huang +1
In text-to-SQL tasks -- as in much of NLP -- compositional generalization is a major challenge: neural networks struggle with compositional generalization where training and test d…